1. Field of the Invention
Plants are classified for evaluation and breeding programs by using remote sensing and image analysis technology. Responses of plant genotypes to environmental variation are determined, and those responses are used to predict the values of commercially useful phenotypic traits resulting from essentially similar genotypic-environmental interactions. Plants selected are for subsequent advancement, manipulations and/or further breeding to improve the trait by altering the gene pool of the plant population.
2. Description of the Related Art
A. Remote Sensing Technology Applied to Plants
In the broad context, remote sensing refers to the capability of obtaining information about an object without touching it. Sensors which are not in direct contact with the object are generally used to obtain the information. In a more limited context, the information obtained by remote sensing is a function of energy emitted by, absorbed by, or reflected from the object.
General principals of remote sensing technology as expressed in methods and apparati, have been applied to collect data on plants. Plant pathologists were among the first to use color infrared photography for remote sensing. A major objective of these early workers was to assess the presence of diseases in trees. Hand held sensors have been used to obtain measures on individual plants, for example, to measure temperature, but these are tedious to use and results are biased due to small samples. One person using a hand gun could perhaps scan 200 plants per day. Concurrent or simultaneous measurements on many plants are not possible, therefore, temporal and spatial variation obscures the basic plant data.
At the other end of the remote sensing distance scale, satellite images of cultivated fields or wild foliage have been produced. The satellite scanning has included crop inventory and acreage estimates. Problems in satellite scanning include low resolution and inadequate area coverage. Clouds and intermittent temporal sampling are also problems in the quality of data obtained in this manner. The distance from which data is obtained by remote sensing varies from inches when a hand held sensor is used, to miles when satellite borne sensors are used. Satellite sensing is not capable of distinguishing among measures of plants of the same species planted in close proximity, e.g., in rows of a-subplot of a field.
Generally, methods employing remote sensing have been applied to assessing the health of individual plants or small groups of plants, or to make assessments of crops on a large scale. Environmental variables such as acreage conditions and soil type have also been determined by remote sensing.
Present progress in applying remote sensing technology to agriculture was summarized at the Beltsville Symposium XV (1990). Related reports have been recently published (1991). The following summary of this research area is based on this publication and on related works.
Previous work has described obtaining remote sensing data on plants and soil from aerial surveillance e.g., satellites, planes, helicopters (Everitt et al., 1990; Williams, 1991; Schmugge et al., 1991; Sequin et al., 1991).
The purposes for obtaining plant data by remote sensing have varied. Most often, global parameters were sought. For example, Sequin et al. (1991) assessed regional crop water conditions using thermal infrared data obtained by satellite and discussed interpretive problems in making those large scale correlations. A number of investigations address how the earth's land-surface vegetation and atmospheric boundary layer interact to affect weather and climate. According to Hall et al. (1991) many problems need to be solved to reach this goal.
Generally, measurements made by remote sensing are physiologically directly or indirectly related to a parameter of interest; e.g., shrinking and swelling of leaf discs or rolling of leaves was found to indicate tissue water status (Spomer and Smith, 1989).
Attempts have been made to forecast crop yield from agricultural regions obtained by remote sensing from satellites. Grain sorghum yield was compared to color infrared film response as measured with a video input image analysis system (Wiegand and Miller, 1987).
Other goals of remote sensing of plants have included documentation of weed or insect infestation, monitoring of water conditions (Everitt et al., 1990; Zhang and Brusewitz, 1990), and detection of crop stress (Stevens et al., 1990).
Little remote sensing has been done in the intermediate range between individual plants and large-area crop conditions. Problems in satellite imaging preclude use of this type of surveillance for detection of plant parameters for small areas; e.g., crop testing subplots or for taking refined quantitative measures (Gutman, 1991; Sequin et al., 1991). Measurement by hand held sensors is not commercially feasible.
Rather than determining plant parameters for their own sake, some studies merely wish to distinguish among species or among types within a species, by remote sensing patterns (Williams, 1991).
Attempts have been made to describe, and in some cases, distinguish among genotypes, by remote sensing measurements (Dhillion et al., 1990; Valdes et al., 1987; 1990; Loffler and Busch, 1983).
Remote sensing data has been reduced to various vegetation indices in efforts to improve analysis (Wiegand et al., 1991; Baret and Guyot, 1991) discuss the potential and limitations of different vegetation indices).
B. Breeding and Evaluation Programs to Improve Plants
Attempts to improve commercially important traits in plants, for example, grain yield in corn and wheat, have consumed the energies of commercial plant breeders in the 1900's. Clever and sophisticated breeding schemes have been devised, yet the rate of improvement of economically important characters has been only a few to several percent of the mean per year for the past several decades. For various crop plants, it has been established that roughly half of this improvement is due to improved husbandry practices, i.e., environmental effects rather than genetic changes effected by selection. (Lande and Thompson, 1990).
The record available from the crude crop breeding programs of the late 1800's through the ever more sophisticated programs leading to the present is littered with dead ends--failures, for one reason or another. For example, data on the ineffectiveness of mass selection for several corn ear characters as presented by Williams and Welton in 1915 are reproduced and discussed by Sprague and Eberhart (1977). Selection for long and short ears was not effective in separating the population into two distinct subpopulations defined by ear length. Yield, one of the most commercially valuable traits, has been the least responsive to selective breeding programs. Selection from 1907-1914 had no overall effect on yield. An examination of data on corn yield trials published by experiment stations in Illinois from 1860 to 1900 shows that many corn varieties were included for short test periods, then discarded because of poor yielding ability. (Sprague and Eberhart, 1977). This article refers to a report that visual selection practiced during inbreeding had little, if any, direct influence on yield in hybrid combinations. However, selection was effective for some other traits, e.g., maturity. Recurrent selection was somewhat more effective in improving breeding populations.
These failures to substantially alter plant characteristics are costly. Even the successes with recurrent selection may generally be described as incremental and long range improvements rather than mercurial saltatory jumps. Divergence of corn varieties for oil and protein content of grain-was achieved if results over the 70 year history of a long-term experiment in Illinois are considered. However, improvement in yield has been less dramatic. Over the past 60 years, increases in yield due to genetic improvement have averaged only about one bushel/acre/year (Hallauer, et al., 1988, p. 466). Only a small population of hybrid plants produced commercially ever show enough improvement to be worth marketing. World-wide needs for plant derived food, both for animals and humans, warrant improved strategies. Plants are also finding uses in non-food products necessitating increased production. New methods are necessary for more efficient and successful plant breeding programs than are currently available.
Molecular genetic techniques are now available for incorporation with classical pedigree-based plant breeding schemes (see discussion in Nienhuis, et al., 1987). The detection and derivation of restriction fragment length polymorphisms (RFLPs) has been useful to develop markers in plants and to determine their associations with quantitative trait loci (QTL) (e.g., in tomatoes, Nienhuis, et al., 1987). Costs of these strategies have been explored by Beckman and Soller (1983). RFLPs were first used as markers in human genetics and since then have been widely applied, in particular, as diagnostic tools to detect genetic disease (Botstein, et al., 1980). One method proposed for integrating molecular genetics with artificial selection for plants and animals is known as marker-assisted selection (MAS) (Lande and Thompson, 1990). For this method of selection, phenotypic trait information is combined with molecular information and is predicted to be more effective than selection based on purely phenotypic selection of the traits of commercial interest, the classical approach.
C. Remote Sensing Technology Applied to Plant Breeding Programs
The related art uses apparatus and basic methods developed for remote sensing, to measure plant variables, notably canopy temperature and multispectral reflectances. However, whatever success has been achieved by others in the past appears to be in distinguishing among land-based objects on a broad, somewhat crude basis, e.g. discrimination among crop types, assessing the condition of acreage. This global assessment has been done mostly by satellites.
With regard to short distance scanning, hand held sensors may be used, e.g., to measure leaf temperature. A leaf or canopy under full irrigation will be cooler than air. As water becomes more limiting, leaf or canopy temperature moves closer to air temperature. Under severe stress, leaf or canopy temperature will exceed air temperature. Calculating the difference between air and leaf temperature is useful to express energy balance in this fashion but air temperature changes during the course of measurement of plot areas, making interpretation of data tenuous due to temporal variation. Remote sensing of large areas, quickly would eliminate this limitation of the method.
One of the challenges of applying new remote sensing technologies to breeding programs designed to improve crops, is how a given measurement of a trait or screening technology may be applied to evaluations of plants growing in fields. The present invention accomplishes the integration of scattered components of remote sensing technology and classic selective breeding strategies to create a method for plant crop improvement. The methods disclosed herein permit high throughput of remote sensing values obtained simultaneously from many plants. Fine resolution to the level of e.g. rows in subplots of fields in which plants are growing, is possible.
Qualitative rather than quantitative assessments have characterized previous agricultural applications of remote sensing. The present invention provides more refined and extensive quantitative measures in plant subplots and in areas within subplots for a novel purpose, e.g. genetic selection and/or identification for breeding and evaluation programs to improve crops. Wide area adaptability of plants (performance predictability, hybrid stability) may be determined.